A nonparametric lack-of-fit test for heteroscedastic regression models

被引：0

作者：

Aubin, Jean-Baptiste ^{[1
]}

Leoni-Aubin, Samuela ^{[1
]}

机构：

[1] INSA Lyon, ICJ, F-69621 Villeurbanne, France

来源：

COMPTES RENDUS MATHEMATIQUE | 2011年 / 349卷 / 3-4期

关键词：

RUNS;

D O I：

10.1016/j.crma.2010.12.009

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

A simple test is proposed for examining the correctness of a given completely specified response function against unspecified general alternatives in the context of univariate regression. The usual diagnostic tools based on residual plots are useful but heuristic. We introduce a formal statistical test supplementing the graphical analysis. Technically, the test statistic is the maximum length of the sequences of ordered (with respect to the covariate) observations that are consecutively overestimated or underestimated by the candidate regression function. Note that the testing procedure can cope with heteroscedastic errors and no replicates. Recursive formulae allowing one to calculate the exact distribution of the test statistic under the null hypothesis and under a class of alternative hypotheses are given. (C) 2010 Academie des sciences. Published by Elsevier Masson SAS. All rights reserved.

引用

页码：215 / 217

页数：3

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